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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Business Analytics with Simulation (CMSE11351)

Course Outline
SchoolBusiness School CollegeCollege of Humanities and Social Science
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryThis course will provide students with the methodologies and methods of simulation, with emphasis on discrete event simulation, to tackle common problems in business analytics.
Course description This course aims at training students in the field of simulation to respond to the job market needs using a variety of methodologies and methods to represent and simulate business environments, test decision rules and assess their performance before their actual implementation. The course covers framing and structuring of managerial problems, and building, verifying, validating and using decision support models to inform better and effective decision making. Emphasis shall be on discrete event simulation with applications concerned with operations and processes in supply chains.
The objective of this course is to enhance students' understanding of the critical nature of building appropriate simulation models as simplified representations of realistic managerial situations, and the role such models play in prescribing solutions to decision making problems. The course also aims at training students to critically assess simulation models and solution methodologies. In addition, students will learn how to use state-of-the-art simulation analytics tools in the context of
decision problems faced by business managers. The course provides opportunities for students to learn from each other, from practitioners in the field, and from the latest theoretical and applied research in the field. The course will require students to work in groups on realistic projects in different business settings involving simulation analytics, and to present their work to the rest of the class and to an external panel when the projects are supplied by industry.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2018/19, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 117 )
Assessment (Further Info) Written Exam 0 %, Coursework 70 %, Practical Exam 30 %
Additional Information (Assessment) Examination
Practical Exams (Individual Assessment) 30% weighting
Term projects 60% weighting
Presentations 10% weighting
- Term projects (60% of the mark including a peer assessment component worth 5%) in which students will have to undertake a simulation project including problem statement/system description, model building, solution design, report on findings, formulation of recommendations and managerial guidelines.
- Presentations (10% of the final mark) involving communication of simulation results/solutions and the methods used to obtain them to demonstrate their ability to address real world problems and to convince their line managers or sponsors to implement the proposed solutions
- Final exam (30% of the mark)
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Discuss the concept and methods of simulation analytics, in general, and discrete event simulation, in particular, using the proper terminology
  2. Identify and properly state decision problems in different business settings, model them using a simulation framework and validate model, choose the right solution methodology and methods and solve them using simulation techniques
  3. Interpret results/solutions in light of the possible courses of action for a given business problem or situation, formulate managerial guidelines and make recommendations
  4. Critically discuss alternative simulation analytics approaches and methods
  5. Communicate solutions effectively and efficiently to a critical audience of non-specialists
Reading List
Law, A.M. (2014) Simulation Modeling and Analysis (5th edition), McGraw-Hill
Kelton, W.D., Sadowski, R.P. and Zupick, N.B. (2014) Simulation with Arena (6th edition) McGraw-Hill
Additional Information
Graduate Attributes and Skills Not entered
Course organiserDr Maurizio Tomasella
Course secretaryMiss Lauren Millson
Tel: (0131 6)51 3013
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